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Hi, I am trying to reproduce your results but am having trouble with MI-FC as i do not have the required fast_cluster_ids.pkl file. I saw quite a bit of discussion in various issues, the closest answer to what I was looking for was this:
Hi @genhao3 - the fast_cluster_ids.pkl is a dictionary that I load for each cancer type, which maps case_id to [M x 1]-dim array of cluster assignments 1⋯C, where M is the number of patches and the indices correspond to the cluster assignment of a given patch embedding. You can use packages like faiss to generate these cluster assignments for running MI-FCN / DeepAttnMISL comparisons.
but it is a bit unspecific and the library mentioned is not straightforward for me. Could you provide either code used to create the file or the .pkl file itself? Any help is much appreciated :)
I know it is a baseline and not your proposed model, but would be interested to run this also.
Best
Valentin
The text was updated successfully, but these errors were encountered:
Hi, I am trying to reproduce your results but am having trouble with MI-FC as i do not have the required fast_cluster_ids.pkl file. I saw quite a bit of discussion in various issues, the closest answer to what I was looking for was this:
but it is a bit unspecific and the library mentioned is not straightforward for me. Could you provide either code used to create the file or the .pkl file itself? Any help is much appreciated :)
I know it is a baseline and not your proposed model, but would be interested to run this also.
Best
Valentin
The text was updated successfully, but these errors were encountered: